Abstract
An imprecise point is a point p with an associated imprecision region \({\mathcal{I}}_p\) indicating the set of possible locations of the point p. We study separability problems for a set R of red imprecise points and a set B of blue imprecise points in \({\Bbb R}^2\), where the imprecision regions are axis-aligned rectangles and each point p ∈ R ∪ B is drawn uniformly at random from \({\mathcal{I}}_p\). Our results include algorithms for finding certain separators (separating R from B with probability 1), possible separators (separating R from B with non-zero probability), most likely separators (separating R from B with maximal probability), and maximal separators (maximizing the expected number of correctly classified points).
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